7 Free Kaggle Micro-Courses for Data Science Beginners

neub9
By neub9
3 Min Read
7 Free Kaggle Micro-Courses for Data Science Beginners
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Many data science beginners face challenges completing lengthy courses. They start strong, but often feel overwhelmed and fail to make progress. However, Kaggle’s micro-courses offer a great alternative for those seeking to learn data science skills without feeling overwhelmed. These courses are designed to only take a few hours to complete, making them ideal for beginners.

The series of micro-courses from Kaggle are beginner-friendly and cover essential topics such as Python, pandas, machine learning, data visualization, SQL, and more. Let’s review some of these courses and what they offer:

Python is an essential language in data science, and the Kaggle Python course covers basics such as syntax, variables, functions, conditionals, lists, loops, strings, dictionaries, and working with external libraries. For those who need an even simpler introduction to programming, there’s an intro to programming course available.

Once you have a grasp of Python, the pandas course will help you learn how to handle data analysis and manipulation using the pandas library. This course covers essential operations on pandas dataframes such as creation, reading, writing, indexing, selecting, renaming, combining, summary functions, and data types.

After mastering Python and pandas, the Data Visualization course focuses on creating informative plots and charts using the Seaborn library. This course includes topics like line charts, bar charts, heat maps, scatterplots, histograms, density plots, and more. It also requires you to work on a final project to apply what you have learned.

The Intro to SQL course is essential for understanding SQL fundamentals and querying datasets using the BigQuery Python client. It covers topics such as selecting, filtering, grouping, joining, and more. For those looking to further advance their SQL skills, there’s also the Advanced SQL course available.

Once you are comfortable with programming and data analysis, you can move on to the Intro to Machine Learning course, which covers how ML models work, data exploration, model validation, underfitting, overfitting, and random forests. After completing this course, you can take the Intermediate Machine Learning course to handle missing values, categorical variables, ML pipelines, cross-validation, XGBoost, and data leakage.

These micro-courses offer a valuable and free learning opportunity for anyone interested in data science. Whether you are a beginner or looking to enhance your skills, Kaggle’s micro-courses can be a great way to acquire essential data science skills. Start your data science journey one micro-course at a time and enjoy learning! Image by Author

Bala Priya C is a developer and technical writer from India, with expertise in DevOps, data science, and natural language processing. She enjoys sharing her knowledge with the developer community through tutorials, how-to guides, and opinion pieces.

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